code: def timing_cuda(model, num_batches, input_features):
      start_event = torch.cuda.Event(enable_timing=True)
      end_event = torch.cuda.Event(enable_timing=True)
      start_event.record()
      for _ in range(num_batches):
          _ = model(input_features)
      end_event.record()
      torch.cuda.synchronize()
      return (
          start_event.elapsed_time(end_event) * 1.0e-3
      ) / num_batches
  
file_path: optimum/tests/benchmark/benchmark_bettertransformer_vit.py
imports: import argparse
  import requests
  import torch
  from PIL import Image
  from transformers import AutoFeatureExtractor, AutoModel
  from optimum.bettertransformer import BetterTransformer
label_desc: Use image node_id 3 for calling a global function with example usage: timing_cuda(model, num_batches, input_features) and returns: unknown